U.S. patent application number 14/137296 was filed with the patent office on 2015-06-25 for tracking electrical appliance usage.
The applicant listed for this patent is THOMSON LICENSING. Invention is credited to Christophe DIOT, Daniel GARNIER-MOIROUX, Anmol Nalin SHETH, Fernando Jorge SILVEIRA FILHO.
Application Number | 20150177292 14/137296 |
Document ID | / |
Family ID | 53399746 |
Filed Date | 2015-06-25 |
United States Patent
Application |
20150177292 |
Kind Code |
A1 |
SILVEIRA FILHO; Fernando Jorge ;
et al. |
June 25, 2015 |
TRACKING ELECTRICAL APPLIANCE USAGE
Abstract
A system for tracking usage patterns of electrical appliances is
disclosed. The system comprises a central database configured to
receive and store information; a plurality of energy sensors each
of the plurality of sensors being configured to measure a change in
electrical energy use by a corresponding one of a plurality of
electrical appliances; at least one presence sensor configured to
determine when at least one user is proximate to the plurality of
electrical appliances and send presence information to the central
database; and a processor configured to extract features from such
information and create at least one user profile corresponding to
the at least one user and a pattern of electrical energy use
associated with the at least one user based on said features.
Inventors: |
SILVEIRA FILHO; Fernando Jorge;
(Palo Alto, CA) ; SHETH; Anmol Nalin; (San
Francisco, CA) ; DIOT; Christophe; (Paris, FR)
; GARNIER-MOIROUX; Daniel; (Paris, FR) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
THOMSON LICENSING |
Issy de Moulineaux |
|
FR |
|
|
Family ID: |
53399746 |
Appl. No.: |
14/137296 |
Filed: |
December 20, 2013 |
Current U.S.
Class: |
702/60 |
Current CPC
Class: |
G01R 19/2513 20130101;
G01R 21/1333 20130101 |
International
Class: |
G01R 21/00 20060101
G01R021/00 |
Claims
1. A system for tracking usage patterns of electrical appliances,
the system comprising a central database configured to receive and
store information from: a plurality of energy sensors connected to
a corresponding one of a plurality of electrical appliances, each
of the plurality of sensors being configured to measure a change in
electrical energy use by the corresponding one of the plurality of
electrical appliances and send appliance monitoring information to
the central database, the appliance monitoring information
including timing information and power consumption information
regarding the electrical energy use; and at least one presence
sensor configured to determine when at least one user is proximate
to the plurality of electrical appliances and send presence
information to the central database the presence information
including timing and identification information regarding the at
least one user; and a processor configured to interact with the
central database to extract features from the appliance monitoring
information and the presence information and create at least one
user profile corresponding to the at least one user and a pattern
of electrical energy use associated with the at least one user
based on the features, wherein the features characterize
interactions between the at least one user and the plurality of
electrical appliances.
2. The system of claim 1, wherein the plurality of energy sensors
include smart plugs or energy meters.
3. The system of claim 1, wherein the plurality of electrical
appliances are heterogeneous and do not cooperate with each
other.
4. The system of claim 1, wherein the change in energy usage
measured by each of the plurality of energy sensors includes a
change in electrical power consumption by each of the plurality of
electrical appliances.
5. The system of claim 1, wherein the at least one presence sensor
is selected from the group consisting of an electronic security key
door lock and a wireless receiver station.
6. The system of claim 1, wherein the presence information includes
an indication that the at least one user has entered close
proximity to the plurality of electrical appliances and an
indication that the at least one user has left close proximity to
the plurality of electrical appliances.
7. The system of claim 1, wherein the processor incorporates a
Support Vector Machine to extract the features and create the user
profiles.
8. A method of tracking usage patterns of electrical appliances,
the method comprising: receiving appliance monitoring information
from a plurality of energy sensors the plurality of energy sensors
being connected to a plurality of electrical appliances and being
configured to measure a change in electrical energy use by the
plurality of electrical appliances the appliance monitoring
information including timing information and power consumption
information regarding the electrical energy use; receiving presence
information from at least one presence sensor the presence sensor
being configured to determine when at least one user is proximate
to the plurality of electrical appliances the presence information
including timing and identification information regarding the at
least one user; and extracting features from the appliance
monitoring information and the presence information, the features
characterizing interactions between the at least one user and the
plurality of electrical appliances; and creating at least one user
profile corresponding to the at least one user and a pattern of
electrical energy use associated with the at least one user based
on said features.
Description
BACKGROUND
[0001] The digital home of the future is envisioned to be a mix of
sensing and computing infrastructure that seamlessly interacts with
the user to enable a wide range of personalized digital home
applications and services. Examples include recommending content by
identifying who is watching television, personalizing the settings
of an appliance based on who is using it, and personalizing the
cooking experience based on who is performing the activity in the
home. A key component of many such applications is a non-intrusive
and seamless user identification and tracking technique to
personalize the experience for the user.
[0002] Existing approaches for user tracking and identification are
cumbersome as they are either limited to individual devices that
require explicit feedback from the user or make use of invasive
sensors like microphones and cameras. Approaches requiring users to
log in or pick a profile are limited to a handful of devices in the
home, like smart TVs and media devices, and are often from the same
manufacturer. Such approaches cannot provide seamless user tracking
and identification across multiple heterogeneous devices in the
home. Other approaches that require the installation of sensors
like cameras and microphones raise several privacy concerns and are
fragile to environmental conditions like poor lighting or
background noise.
SUMMARY
[0003] In view of the foregoing background, a system for tracking
usage patterns of electrical appliances is disclosed. The system
includes a central database configured to receive and store usage
information, such as energy consumption information, timing
information, and user identification and presence information. The
system also includes a plurality of energy sensors connected to a
plurality of electrical appliances, with each of the plurality of
sensors being configured to measure a change in electrical energy
use by a corresponding one of the plurality of electrical
appliances. The plurality of energy sensors send appliance
monitoring information to the central database, wherein the
appliance monitoring information includes timing information and
power consumption information regarding the electrical energy
use.
[0004] Also included is at least one presence sensor that is
configured to determine when at least one user is proximate to the
plurality of electrical appliances. The presence sensor sends
presence information to the central database, wherein the presence
information includes timing and identification information
regarding the at least one user. The system further includes a
processor configured to extract features that from the appliance
monitoring information and the presence information that
characterize interactions between the at least one user and the
plurality of electrical devices, and create at least one user
profile corresponding to the at least one user based on the
features.
[0005] Also disclosed is a method for tracking usage patterns of
electrical appliances. The method includes receiving appliance
monitoring information from a plurality of energy sensors, the
plurality of energy sensors being connected to a plurality of
electrical appliances and being configured to measure a change in
electrical energy use by the plurality of electrical appliances,
the appliance monitoring information including timing information
and power consumption information regarding the electrical energy
use; receiving presence information from at least one presence
sensor, the presence sensor being configured to determine when at
least one user is proximate to the plurality of electrical
appliances, the presence information including timing information
and power consumption information regarding the electrical energy
use; and extracting features from the appliance monitoring
information and the presence information, the features
characterizing interactions between the at least one user and the
plurality of electrical devices; and creating at least one user
profile corresponding to the at least one user based on the
features.
BRIEF DESCRIPTION OF THE DRAWINGS
[0006] For a more complete understanding of the present invention,
reference is made to the following detailed description of an
embodiment considered in conjunction with the accompanying
drawings, in which:
[0007] FIG. 1 is a diagram showing a room in which a system for
tracking usage patterns in electrical appliances in accordance with
an embodiment of the present invention is employed; and
[0008] FIG. 2 is a flow chart showing a method of tracking usage
patterns in electrical appliances in accordance with an embodiment
of the present invention.
DETAILED DESCRIPTION
[0009] The present disclosure relates to a system for user
identification and tracking with respect to electrical appliance
use, such as, for example, kitchen and bathroom appliances. The
system is able to identify which users use a particular electrical
appliance by profiling and learning the unique appliance usage
patterns across the different users having access to the room in
which the electrical appliance resides. Appliance usage information
is obtained by monitoring the energy consumption of individual
appliances using smart meters and/or distributed smart plugs.
[0010] It should be understood that the elements shown in the
figures may be implemented in various forms of hardware, software
or combinations thereof. Preferably, these elements are implemented
in a combination of hardware and software on one or more
appropriately programmed general-purpose devices, which may include
a processor, memory and input/output interfaces. Other elements can
be implemented through the use of specifically-purposed devices,
such as electronic display screens and electronic sensors.
[0011] FIG. 1 illustrates a system 100 constructed in accordance
with an embodiment of the present invention. The system includes a
plurality of energy sensors 102a, 102b that are connected to a
corresponding number of electrical appliances 104a, 104b. The
electrical appliances 104a, 104b can include any commonly used
electrical appliance, including kitchen appliances such as, for
example, a microwave oven or a coffee maker (as seen in FIG. 1),
entertainment appliances such as, for example, a television or a
video game console, bathroom appliances, and/or appliances commonly
associated with an office setting. The energy sensors 102a, 102b
collect energy consumption data, which includes information
regarding the time one of the electrical appliances 104a, 104b was
used and how much energy was consumed by the appliance during that
time. This energy consumption data is then transmitted to a central
database 106 for processing. In one embodiment, the plurality of
energy sensors 102a, 102b include smart meters and/or distributed
smart plugs.
[0012] Still referring to FIG. 1, the system 100 also includes at
least one presence sensor that detects and records the presence of
a person entering the room in which the electrical appliances 104a,
104b reside. In one embodiment, the presence sensor is an
electronic security key door lock 108 that is opened by an external
key fob. In another embodiment, the presence sensor is a wireless
receiver station that reads the media address control (MAC) address
of the various smart phones in the area and records their presence.
The at least one presence sensor identifies the name and time of
each user entering the room, as well as the time in which the user
enters the room, and contemporaneously transmits such information
to the central database 106 for processing. In one embodiment, the
at least one presence sensor 108 also identifies when a user leaves
after entering.
[0013] The system 100 also includes the central database 106
referenced above, which includes a memory and a processor. The
central database 106 is configured to receive and record
information transmitted from the plurality of energy sensors 102a,
102b and the at least one presence sensor. The central database 106
also uses such information to create user profiles for each of the
users identified in the presence data that indicate each user's
pattern of behavior when using the electrical appliances 102a,
102b. In one embodiment, the central database employs Support
Vector Machines ("SVMs") that learn the per-appliance usage
patterns of the users to build the user profiles.
[0014] FIG. 2 illustrates a method of tracking usage patterns of
electrical appliances in accordance with an embodiment of the
present invention. The method begins with a user entering close
proximity to the electrical appliances 104a, 104b (step 202). The
presence sensor senses the user's entrance and sends a signal to
the central database noting the time of entrance and the identity
of the user (step 204). In the embodiment shown in FIG. 1, this is
accomplished by the user, for example, unlocking the security key
door lock 108 to the door through use of a personalized key fob,
and the security key door lock 108 noting the identity of the user
and the time of the user's entrance through the unique signal
received from the user's key fob.
[0015] Thereafter, the user begins using one or more of the
electrical appliances 104a, 104b (step 206). These energy sensors
102a, 102b measure the changes in electrical energy use by the
electrical appliances 104a, 104b associated with the user's use.
The energy sensors then transmit signals including appliance
monitoring information to the central database 106, wherein such
appliance monitoring information notes the amount of each change in
energy use and the timing of each change in energy use (step
208).
[0016] The central database receives the appliance monitoring
information and the presence information from the energy sensors
and the presence sensor, respectively (step 210). The system then
extracts features from the energy consumption and presence
information collected at the central database (step 212). These
features characterize the interactions between the user and the
electrical appliances.
[0017] For example, the presence information can indicate that User
A entered the room in FIG. 1 at time X, while the appliance
monitoring information can include changes in electrical energy
usage by the electrical appliances 104a, 104b that occurred within
Y seconds after User A's presence was recorded at time X. This
information would indicate that between time X and time X+Y, the
user was making use of the electrical appliances 104a, 104b.
Furthermore, the appliance monitoring information can indicate how
long User A was using the electrical appliances 104a, 104b based on
the degrees of change in energy consumption occurring from between
time X and time X+Y. Further such features can be aggregated with
the previous example of features to identify patterns of behavior
associated with User A that can be used to predict when and for how
long User A will use the electrical appliances 104a, 104b.
[0018] With the desired features extracted from the appliance
monitoring information and the presence information, the system can
create user profiles associated with the identified users of the
electrical appliances 104a, 104b (step 214). These user profiles
show patterns of behavior associated with the users identified by
the presence sensor over time. The user profiles can then be used
to predict electrical appliance usage by a particular user whenever
the user is identified.
[0019] The systems and methods disclosed herein carry many benefits
over prior systems. For example, the system's energy sensors are
easy to use. Smart plugs and energy meters can be used to serve as
such sensors, and they are simple to install in a home or office
setting. Such devices are also inexpensive and do not require
replacing batteries because they connect to the electrical
appliance's power source. In addition, the disclosed system
provides support for heterogeneous appliances. Identifying
appliance usage by monitoring their energy consumption does not
require any cooperation between the appliances, thereby allowing
the system to operate seamlessly across heterogeneous appliances in
a home or office setting. Furthermore, the disclosed system is
transparent to the user and does not require any explicit feedback
from the user.
[0020] The various embodiments disclosed herein can be implemented
as hardware, firmware, software, or any combination thereof.
Moreover, the software is preferably implemented as an application
program tangibly embodied on a program storage unit or computer
readable medium. The application program may be uploaded to, and
executed by, a machine comprising any suitable architecture.
Preferably, the machine is implemented on a computer platform
having hardware such as one or more central processing units
("CPUs"), a memory, and input/output interfaces. The computer
platform may also include an operating system and microinstruction
code. The various processes and functions described herein may be
either part of the microinstruction code or part of the application
program, or any combination thereof, which may be executed by a
CPU, whether or not such computer or processor is explicitly
shown.
[0021] All examples and conditional language recited herein are
intended for pedagogical purposes to aid the reader in
understanding the principles of the invention and the concepts
contributed by the inventor to furthering the art, and are to be
construed as being without limitation to such specifically recited
examples and conditions. Moreover, all statements herein reciting
principles, aspects, and embodiments of the invention, as well as
specific examples thereof, are intended to encompass both
structural and functional equivalents thereof. Additionally, it is
intended that such equivalents include both currently known
equivalents as well as equivalents developed in the future, i.e.,
any elements developed that perform the same function, regardless
of structure.
[0022] It will be understood that the embodiments described herein
are merely exemplary and that a person skilled in the art may make
many variations and modifications without departing from the spirit
and scope of the invention. All such variations and modifications
are intended to be included within the scope of the invention as
defined in the appended claims.
* * * * *